# A Methodology for Information Flow Experiments

arXiv: https://arxiv.org/abs/1405.2376 · HTML: https://mlsanity.com/paper/1405.2376/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2014.

## Built on by (most cited first, 1 of 1)

- [What is Proxy Discrimination?](https://mlsanity.com/paper/2205.05265/) (2022)

## Abstract (arXiv)

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the usage of data by websites. We prove that these problems are ones of causal inference. Leveraging this connection, we push beyond traditional information flow analysis to provide a systematic methodology based on experimental science and statistical analysis. Our methodology allows us to systematize prior works in the area viewing them as instances of a general approach. Our systematic study leads to practical advice for improving work on detecting data usage, a previously unformalized area. We illustrate these concepts with a series of experiments collecting data on the use of information by websites, which we statistically analyze.